What this category of data consists of
Reference only; verify against the target FastGPT release and deployment documentation.
What constraints these characteristics impose on the workflow orchestration link
Data sources span multiple independent systems. Configure workflows to include cross-system data fetch nodes. Unify data formats from all sources before running summary operations. The annual update cycle restricts workflow runs to the budget preparation window. This prevents non-periodic invalid triggers. Most document fields follow financial professional specifications. Pre-set dedicated fields in workflow variables to reduce manual mapping errors. Subordinate unit ledgers require batch summary. Configure workflows to support loop processing of array-type inputs. This supports merging logic for multi-item data.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Trigger Timing | Launch during the annual budget preparation window, run only from October to February of the following year (per actual testing) | Matches the annual update frequency requirement of this category, avoids non-periodic invalid operation |
Input variables variables | Preset 4 types of fields: personnel expenses, project expenditures, performance targets, unit establishment numbers | Aligns with the standard field structure of documents in this category, reduces data mapping errors |
| Loop Node Configuration | Process 1-5 subordinate unit data items per single loop | Adapts to the batch summary requirement for subordinate unit ledgers, avoids excessive load on a single node |
Target Node nodeId | Bind the unique ID of the budget report generation node | Ensures correct call links between workflow nodes, avoids node matching errors |
| Failure Retry Count | 2 retries, 60-second retry interval | Handles temporary network fluctuations when fetching data across systems |
| Result Export Format | Excel format following the department budget approval template | Matches document requirements for downstream review links |
Three common configuration errors
- Incorrect array format input for loop nodes, leading to failed processing of single data items. Symptoms include empty output from the loop node or only partial items being processed. Causes include failure to correctly convert subordinate unit ledger data into array-format input parameters, and failure to match the array input requirements of the loop node.
- Failure to configure a result export node, leading to generated ledgers and reports that cannot be submitted for review. Symptoms include no available output files after workflow runs complete. Causes include failure to add a result export step, and failure to convert summarized data into the standard format required for department budget preparation.
- Failure to call AI content generation with budget preparation context, leading to non-compliant reports. Symptoms include generated budget reports missing performance targets or project expenditure details. Causes include failure to preset dedicated budget preparation rules in the workflow, and failure to use historical final accounts data from
variablesas context supplements.
How to confirm proper configuration
- Trigger a test run of the workflow, check if the loop node processes all subordinate unit ledger data as expected, confirm that array-format input parameters are correctly recognized.
- Review logs from the data source validation step, confirm that all input data passes field format validation with no format error prompts.
- Export the report generated by the workflow, compare against the standard document structure for department budget preparation, confirm that all preset fields have been populated.
- Call the test model to generate a single report, confirm that the output content complies with general budget preparation specifications, with no missing key fields.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.